Rows: 201
Columns: 36
$ school_id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
$ school_name <chr> "Національний технічний університет Україн…
$ rank_2024 <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
$ index_2024 <dbl> 4.66, 4.94, 5.14, 5.93, 5.98, 7.43, 11.12, 11…
$ qs_rank <dbl> 3, 1, 4, 2, 4, 5, 6, 4, 5, 5, 7, 7, 4, 7, 7, …
$ qs_index <dbl> 0.45, 0.15, 0.60, 0.30, 0.60, 0.75, 0.90, 0.6…
$ scopus_rank <dbl> 5, 1, 9, 2, 6, 3, 21, 11, 4, 24, 30, 7, 23, 3…
$ scopus_index <dbl> 0.65, 0.13, 1.17, 0.26, 0.78, 0.39, 2.73, 1.4…
$ webometrics_rank <dbl> 1, 3, 11, 9, 2, 10, 6, 8, 32, 7, 20, 15, 37, …
$ webometrics_index <dbl> 0.1, 0.3, 1.1, 0.9, 0.2, 1.0, 0.6, 0.8, 3.2, …
$ uimpact_rank <dbl> 5, 6, 2, 4, 1, 5, 6, 4, 4, 4, 6, 5, 6, 4, 6, …
$ uimpact_index <dbl> 0.625, 0.750, 0.250, 0.500, 0.125, 0.625, 0.7…
$ wur_rank <dbl> 4, 4, 2, 4, 1, 4, 5, 4, 6, 3, 6, 4, 6, 6, 6, …
$ wur_index <dbl> 0.60, 0.60, 0.30, 0.60, 0.15, 0.60, 0.75, 0.6…
$ qswur_rank <dbl> 4, 6, 1, 3, 2, 5, 9, 7, 9, 8, 9, 9, 9, 9, 9, …
$ qswur_index <dbl> 0.500, 0.750, 0.125, 0.375, 0.250, 0.625, 1.1…
$ competition_rank <dbl> 1, 3, 2, 8, 4, 5, 7, 16, 11, 30, 9, 14, 13, 2…
$ competition_index <dbl> 0.055, 0.165, 0.110, 0.440, 0.220, 0.275, 0.3…
$ naqa_rank <dbl> 1, 2, 3, 10, 8, 7, 4, 66, 9, 28, 6, 78, 13, 1…
$ naqa_index <dbl> 0.055, 0.110, 0.165, 0.550, 0.440, 0.385, 0.2…
$ patent_rank <dbl> 5, 16, 2, 17, 14, 27, 4, 11, 32, 24, 21, 28, …
$ patent_index <dbl> 0.275, 0.880, 0.110, 0.935, 0.770, 1.485, 0.2…
$ mean_rank <dbl> 24.5, 20.0, 22.0, 19.5, 44.5, 23.5, 62.5, 30.…
$ mean_index <dbl> 1.348, 1.100, 1.210, 1.073, 2.448, 1.293, 3.4…
$ school_abb <chr> "KPI", "KNUTS", "LKPI", "HNUK", "SSU", "LNU",…
$ student_count <dbl> 40500, 25000, 35000, 16000, 14000, 19357, 390…
$ city <chr> "Kyiv", "Kyiv", "Lviv", "Kharkiv", "Sumy", "L…
$ oblast <chr> "Kyiv", "Kyiv", "Lviv", "Kharkiv", "Sumy", "L…
$ region <chr> "North", "North", "West", "East", "North", "W…
$ profile <chr> "polytechnic", "general", "polytechnic", "gen…
$ department_count <dbl> 19, 14, 16, 21, 8, 19, 13, 10, 11, 8, 9, 12, …
$ program_count <dbl> 118, 198, 64, 115, 55, 198, 32, 90, 44, 25, 4…
$ city_population <dbl> 3020000, 3020000, 721301, 1418980, 271000, 72…
$ application_total_count <dbl> 30156, 29812, 31641, 11206, 4075, 31190, 1033…
$ score_mean <dbl> 159.3, 162.3, 160.0, 164.1, 161.1, 159.4, 148…
$ application_budget_count <dbl> 21488, 19616, 21969, 7261, 2991, 21576, 6622,…Comparing ‘Top’ and Local Universities in Ukraine
Oleksandr Koval
Introduction
Story of Creating
Why did I create this presentation?
There are lots of opportunities to continue your education nowadays. If you used to have only a few main universities to attend, now almost every region has its local universities offering different specializations. So, where would you go?
“TOP UNIVERSITIES” VS LOCAL UNIVERSITY
Short introduction
As a top university, I took three of the biggest Ukrainian national universities that have a strong base of all specializations. As a local one, I took polytechnic universities that are located in the big cities of Ukraine (Dnipro, Odesa, Vinnytsia) but we can’t name them “top”.
OUR GUESTS
Team “TOP UNIVERSITIES”:
- KPI
- KNUTS
- LKPI
Team “Local universities”:
- VNTU
- NTUDP
- NUOPL
Location
Map of key “Top” and Local Universities in Ukraine
By the end, we want to know…
- Is a “top” university really worth it ?
- Where would be better to go ?
- Why “top” university is “Top” ?
- Is a local university worth it ?
- Where will you find your dream ?
Data overview
Data Overview
All information was taken from 1-scribe
It contains all used data in this presentation
Data Overview
Source: 1-scribe-ds3.rds
Main table: ds3
Rows: 200
Columns: 36
Columns that we use: rank_2024, qs_rank, scopus_rank, webometrics_rank, wur_rank, qswur_rank, school_abb, student_count, city, application_total_count, application_budget_count, score_mean
Data Overview
ds3 - data %>% glimpse()
Data Overview
ds3 - data %>% summary()
school_id school_name rank_2024 index_2024
Min. : 1.0 Length:201 Min. : 1.0 Min. : 4.66
1st Qu.: 51.0 Class :character 1st Qu.: 51.0 1st Qu.:28.00
Median :101.0 Mode :character Median :101.0 Median :42.60
Mean :100.6 Mean :100.6 Mean :40.30
3rd Qu.:150.0 3rd Qu.:150.0 3rd Qu.:53.34
Max. :200.0 Max. :200.0 Max. :66.42
qs_rank qs_index scopus_rank scopus_index
Min. :1.000 Min. :0.150 Min. : 1.0 Min. : 0.13
1st Qu.:7.000 1st Qu.:1.050 1st Qu.: 51.0 1st Qu.: 6.63
Median :7.000 Median :1.050 Median :101.0 Median :13.13
Mean :6.831 Mean :1.025 Mean :101.7 Mean :13.22
3rd Qu.:7.000 3rd Qu.:1.050 3rd Qu.:150.0 3rd Qu.:19.50
Max. :7.000 Max. :1.050 Max. :202.0 Max. :26.26
webometrics_rank webometrics_index uimpact_rank uimpact_index
Min. : 1.0 Min. : 0.10 Min. :1.000 Min. :0.1250
1st Qu.: 51.0 1st Qu.: 5.10 1st Qu.:6.000 1st Qu.:0.7500
Median :101.0 Median :10.10 Median :6.000 Median :0.7500
Mean :102.6 Mean :10.26 Mean :5.657 Mean :0.7071
3rd Qu.:150.0 3rd Qu.:15.00 3rd Qu.:6.000 3rd Qu.:0.7500
Max. :236.0 Max. :23.60 Max. :6.000 Max. :0.7500
wur_rank wur_index qswur_rank qswur_index
Min. :1.000 Min. :0.1500 Min. :1.000 Min. :0.125
1st Qu.:6.000 1st Qu.:0.9000 1st Qu.:9.000 1st Qu.:1.125
Median :6.000 Median :0.9000 Median :9.000 Median :1.125
Mean :5.846 Mean :0.8769 Mean :8.821 Mean :1.103
3rd Qu.:6.000 3rd Qu.:0.9000 3rd Qu.:9.000 3rd Qu.:1.125
Max. :6.000 Max. :0.9000 Max. :9.000 Max. :1.125
competition_rank competition_index naqa_rank naqa_index
Min. : 1.0 Min. :0.055 Min. : 1.00 Min. :0.055
1st Qu.:27.0 1st Qu.:1.485 1st Qu.: 46.00 1st Qu.:2.530
Median :31.0 Median :1.705 Median : 77.00 Median :4.235
Mean :29.7 Mean :1.633 Mean : 82.16 Mean :4.519
3rd Qu.:36.0 3rd Qu.:1.980 3rd Qu.:120.00 3rd Qu.:6.600
Max. :36.0 Max. :1.980 Max. :163.00 Max. :8.965
patent_rank patent_index mean_rank mean_index
Min. : 1.00 Min. :0.055 Min. : 19.50 Min. : 1.073
1st Qu.:29.00 1st Qu.:1.595 1st Qu.: 68.50 1st Qu.: 3.768
Median :36.00 Median :1.980 Median : 94.00 Median : 5.170
Mean :31.21 Mean :1.717 Mean : 95.22 Mean : 5.237
3rd Qu.:37.00 3rd Qu.:2.035 3rd Qu.:120.00 3rd Qu.: 6.600
Max. :37.00 Max. :2.035 Max. :201.00 Max. :11.055
school_abb student_count city oblast
Length:201 Min. : 178 Length:201 Length:201
Class :character 1st Qu.: 4000 Class :character Class :character
Mode :character Median : 6000 Mode :character Mode :character
Mean : 8371
3rd Qu.:10000
Max. :40500
NA's :4
region profile department_count program_count
Length:201 Length:201 Min. : 5.00 Min. : 6.00
Class :character Class :character 1st Qu.: 6.00 1st Qu.: 25.00
Mode :character Mode :character Median : 8.00 Median : 35.00
Mean : 9.32 Mean : 46.30
3rd Qu.:11.00 3rd Qu.: 54.75
Max. :21.00 Max. :198.00
NA's :151 NA's :151
city_population application_total_count score_mean
Min. : 24000 Min. : 53.0 Min. :139.5
1st Qu.: 271000 1st Qu.: 931.2 1st Qu.:147.3
Median : 721301 Median : 2152.0 Median :151.3
Mean :1131621 Mean : 3531.8 Mean :153.5
3rd Qu.:1418980 3rd Qu.: 3964.2 3rd Qu.:157.7
Max. :3020000 Max. :31641.0 Max. :193.3
NA's :7 NA's :8
application_budget_count
Min. : 39.0
1st Qu.: 610.5
Median : 1443.0
Mean : 2499.4
3rd Qu.: 3017.5
Max. :21969.0
NA's :34 Rating system
Chapters of this presentation
- 🌍 The importance of location
- 📝 Chances to get in
- 🏆 National rank
- 🏙️ Local university comparison:
- Local rank
- Local size
- Local score to apply
- 🌐 International attitude
1 | The importance of location
Imagine that you just graduated from school. You passed your exams very well.
The first thing you note when you are looking at your future university is the city, where it’s located.
Map of the Local Universities
Why it is so important?
Your university city is not just about education – it’s your lifestyle for 4–6 years.
Think about how you will live without your friends and family.
What would you do if something went wrong?
Are you the kind of person who can make new friends quickly, or not?
PROS & CONS BIG CITY
Think logically: Big city = big opportunities
In a big city, there are more chances to be noticed by big or international companies
Universities are more modern, with stronger academic programs
Risk of “getting lost in the crowd”
Expensive accommodation, food, and entertainment
Higher competition for entry and during studies, making it harder to stand out
PROS & CONS LIVING HOME
It is your home!
- Familiar city, close to your family and friends. They can help you and support you in trouble
- You haven’t got a “period of adaptation” or it would be far shorter than in a big city
- You may have “the feeling of missed opportunity”
- You have fewer contacts with international companies
- Less perspective than in a big city
Overall
Living in a big city can be hard, and for some people, it can be very difficult to meet new friends or live alone. However, for everyone, it is a very useful experience that absolutely must be felt by all young adults.
Living in your hometown is easier, and you don’t need to make as much effort in your daily life. It is more stable.
2 | Chances to get in
The second thing you check after considering the city is whether you have the opportunity to become part of the team.
How many other people are thinking the same as you?
What if you are short of money?
Will your average score be enough?
№1 Total number of applications
№2 Number of applications on Budget
№3 Number of budget applications to non-budget
№3-1 Number of budget applications to non-budget
№4 The average score
3 | National Rank
What is it?
The national rank according to EuroOsvita is the most authoritative rank in the country. We have over 200 universities in this rank. This rank is based on different ranks, including foreign and national.
“Top” Universities VS Local
4 | Comparing Locally
When you have checked your chances to get in and seen the big picture, what do you want to do next?
In my opinion, it’s a good idea to consider other university options in your city.
In this chapter, we compare all universities in Odesa, Vinnytsia, and Dnipro.
Universities in the Vinnytsia | EuroOsvita
Universities in the Vinnytsia | Number of Students
Universities in the Vinnytsia | Average score
In Odesa
Universities in the Odesa | EuroOsvita
Universities in the Odesa | Number of Students
Universities in the Odesa | Average score
In Dnipro
Universities in the Dnipropetrovsk | EuroOsvita
Universities in the Dnipropetrovsk | Number of Students
Universities in the Dnipropetrovsk | Average Score
4 | International Attitude
What is it?
The last thing that can insure you to apply is the international attitude. We are going to compare universities by different international ranks (that are already included in the main “National Rank”).
We are comparing according to:
- Scopus Rank
- QS Rank
- Webometrics Rank
- THE World University Ranking
- QS Sustainability Ranking
Scopus Rank
Qs Rank
Webometrics Rank
The World University Ranking
QS Sustainability Ranking
Summary
Honestly, it is so hard to choose one university. This is a very important decision in your life that will determine the next 4–5 years of your life, your future friends, and possibly your whole future career. It sounds very serious, doesn’t it?
The author of this presentation advises all students who don’t know which university to choose: you have already seen all the advantages and disadvantages, all the info about locations, rankings, and other analytics—so just choose how you feel/